Name history
| Warp | |
| Jelly | |
| Warp Trotter | |
| Numby | |
| INFAMØUS/Warp | |
| MERRY CHRISTMAS | |
| CLIVE NEED BUFF | |
| Tekken Noob | |
| Newbie Fatboy | |
| Lars Practice | |
| Boom Boom Pow | |
| Mokujin Main |
| Warp vs Panda | 44–48 | 47.83% |
| Warp vs Kazuya | 60–30 | 66.67% |
| Warp vs King | 53–22 | 70.67% |
| Warp vs Reina | 45–29 | 60.81% |
| Warp vs Jin | 53–16 | 76.81% |
| Warp vs Bryan | 37–26 | 58.73% |
| Warp vs Law | 38–23 | 62.30% |
| Warp vs Lidia | 30–28 | 51.72% |
| Warp vs Lee | 37–16 | 69.81% |
| Warp vs Hwoarang | 37–14 | 72.55% |
| Warp vs Dragunov | 37–14 | 72.55% |
| Warp vs Eddy | 34–14 | 70.83% |
| Warp vs Heihachi | 35–13 | 72.92% |
| Warp vs Yoshimitsu | 27–17 | 61.36% |
| Warp vs Feng | 31–13 | 70.45% |
| Warp vs Lars | 28–15 | 65.12% |
| Warp vs Steve | 31–11 | 73.81% |
| Warp vs Clive | 23–19 | 54.76% |
| Warp vs Lili | 33–8 | 80.49% |
| Warp vs Paul | 22–17 | 56.41% |
| Warp vs Alisa | 25–10 | 71.43% |
| Warp vs Raven | 18–16 | 52.94% |
| Warp vs Xiaoyu | 27–6 | 81.82% |
| Warp vs Devil Jin | 19–14 | 57.58% |
| Warp vs Azucena | 18–15 | 54.55% |
| Warp vs Fahkumram | 24–5 | 82.76% |
| Warp vs Victor | 20–6 | 76.92% |
| Warp vs Asuka | 18–7 | 72.00% |
| Warp vs Jun | 13–11 | 54.17% |
| Warp vs Nina | 12–11 | 52.17% |
| Warp vs Zafina | 10–11 | 47.62% |
| Warp vs Jack-8 | 11–9 | 55.00% |
| Warp vs Shaheen | 12–7 | 63.16% |
| Warp vs Leroy | 9–10 | 47.37% |
| Warp vs Armor King | 12–7 | 63.16% |
| Warp vs Leo | 10–7 | 58.82% |
| Warp vs Claudio | 11–3 | 78.57% |
| Warp vs Kuma | 11–3 | 78.57% |
| Warp vs Anna | 5–6 | 45.45% |
| Warp vs Miary Zo | 2–3 | 40.00% |
Limitations
This data is often requested to give insight into which characters you have more trouble with than others, but it is not particularly helpful for that. The main issue is that it is heavily skewed by how strong the opponents you play are.
For example, this data suggests my worst matchup is clearly vs Reina, but that's just because most of those games are vs Yagami.
There is a way to account for this being worked on. The central idea is to assign each matchup a rating vs you which adjusts based on the result, much like the regular rating but also based on the rating of each player. With this, it would give a better summary of how well you perform vs each character.
In the meantime, this page is here to present the data as requested.